Motion video can be represented by a digital signal in which a series of bits of information represent each video frame. As more bits of information are required to represent each frame, the cost and complexity of the hardware necessary to process the signals as well as the delay in processing the signal are increased.
Image compression is a process which allows the digital signals representing images, such as frames of a motion video, to be transmitted in a coded form over a communications channel or to be stored on a medium, such as a CD ROM, using fewer bits of data than would be required for an uncoded image. Image compression is based on the removal of redundant data. Because the storage and transmission of digital video signals is central to many applications, and because an uncompressed representation of a video signal requires a large amount of bitspace, either in storage or transmission, the use of digital video compression techniques is vital to this advancing art.
Noise in video signals degrades both the image quality and the performance of subsequent coding operations by creating random fluctuations in the bit information thereby reducing the redundancy, and making coding of the later pictures less efficient since there are more "changes" from frame to frame. Consequently, eliminating noise improves the efficiency of coding as well as the final picture quality.
The present invention relates to noise reduction, particularly, temporal noise reduction. Temporal noise can be reduced by simple frame averaging, as described by S. Lim, Two Dimensional Signal Processing and Image Processing pp. 468-476 (Prentice Hall 1990), incorporated herein by reference. When the images in the motion video are static, this is an effective technique. When the image is moving, however, simple frame averaging blurs moving objects, which reduces the image resolution.
In another method, explained in B. G. Haskell, P. L. Gordon, R. L. Schmidt and J. V. Scattaglia, IEEE Trans. on Communications, Vo. Com-25, No. 11 1977, incorporated herein by reference, a motion detector is used to distinguish the stationary areas in each frame of a motion video sequence from the moving area in that frame. Noise reduction techniques (or filtering) are applied only in the stationary area. This method is easily implemented but does not reduce noise in the moving area.
Other methods of noise reduction use motion information to permit noise reduction in the moving area. See E. Dubois and S. Sabri, Noise Reduction in Image Sequencing Using Motion-Compensated Temporal Filtering, IEEE Trans. on Communications, Vol. Com-32, No. 7, 1988 (using two frame temporal support and one directional motion compensation); J. M. Boyce, Noise Reduction of Image Sequences Using Adaptive Motion Compensated Frame Averaging, SPIE Proceedings, Vol. 3, pp. 461-464, 1992 (using small block size), both incorporated herein by reference. The first method is limited in that it uses only two frames for filtering. The second method requires additional motion estimation and added frame storage, thus increasing the cost and complexity of the hardware required for filtering.